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Record W2944343596 · doi:10.1029/2018ja026413

Dependence of Whistler Mode Chorus Wave Generation on the Maximum Linear Growth Rate

2019· article· en· W2944343596 on OpenAlexaff
Rongxin Tang, Danny Summers

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMemorial University of Newfoundland
FundersNational Natural Science Foundation of China
KeywordsChorusPhysicsMagnetosphereBoundary (topology)Computational physicsWhistlerElectronMathematical analysisMathematicsQuantum mechanicsPlasma

Abstract

fetched live from OpenAlex

Abstract Whistler mode chorus waves play a key role in controlling electron dynamics in Earth's inner magnetosphere. A criterion has been previously suggested whereby if the maximum value of the linear growth rate of whistler mode waves exceeds a certain critical bound, then fully nonlinear wave growth occurs and chorus waves are generated. This criterion corresponds to a boundary curve in (Nh/N0,AT) space where Nh is the hot electron number density, N0 is the cold electron number density, and AT is the thermal anisotropy. Chorus waves are generated in the region above the boundary curve, while no chorus waves are generated below the boundary curve. In the present study, we make use of a recently published set of 36 particle simulations of chorus, and we thereby are able to confirm the validity of the criterion. It is expected that this simple concept of the theoretical boundary curve based on linear theory will be useful in guiding the choice of parameters in future simulations of chorus and also of practical use in interpreting experimental chorus wave data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.310
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2019
Admission routes1
Has abstractyes

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